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A Comparison of wavelet and curvelet for lung cancer diagnosis with a new Cluster K-Nearest Neighbor classifier

机译:使用新的簇K最近邻分类器对小波和曲线波进行肺癌诊断的比较

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This paper presents a comparison of wavelet and curvelet for lung cancer in term of diagnostic accuracy when each one is applied separately to the cluster K-Nearest neighbor classifier. Lung cancer is among the diseases that lead to high mortality rate globally. The computer aided diagnoisis system that is shown in this paper consists of a preprocessing state, a feature extraction stage (wavelet or curvelet), a feature selection stage and finally a classification stage. The results obtained on the x-ray dataset that was utilized suggest that wavelet produce better accuracy with low false positives and false negatives compared to curvelet.
机译:本文将小波和Curvelet小波对肺癌的比较(当将每个小波和Curvelet小波分别应用于聚类K最近邻居分类器时)在诊断准确性上进行比较。肺癌是导致全球高死亡率的疾病之一。本文显示的计算机辅助诊断系统包括预处理状态,特征提取阶段(小波或曲线波),特征选择阶段以及最后的分类阶段。在X射线数据集上获得的结果表明,与Curvelet相比,小波产生了更高的准确度,且误报率和误报率较低。

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